MC-NN: An End-to-End Multi-Channel Neural Network Approach for Predicting Influenza A Virus Hosts and Antigenic Types

Influenza poses a significant threat to public health, particularly among the elderly, young children, and people with underlying dis-eases. The manifestation of severe conditions, such as pneumonia, highlights importance preventing spread influenza. An accurate cost-effective prediction host antigenic sub-types influenza A viruses is essential addressing this issue, in resource-constrained regions. In study, we propose multi-channel neural network model predict subtypes from hemagglutinin neuraminidase protein sequences. Our was trained on comprehensive data set complete sequences evaluated various test sets incomplete results demonstrate potential practicality using networks predicting both full partial